R&D to Develop an Asset Management System


Nelson Point, WA

Project Overview

The client wanted to reduce the time required by the maintenance coordinators to plan the remediation of structural defects for all Pilbara assets. This process was being done manually and included downloading different files to collate different layers of information, filter, sort, and cross-reference the data, in order to classify defects before the workflow proceeded to resourcing and scheduling of the remediations. This created siloing of the work process between departments, resulting in end-to-end process conflicts, inefficiencies, unnecessary revisions, as well as failed deadlines and incorrect remediation scopes.

The objective of the project was to develop a planning tool in VBA programming language to automate the extraction and classification of information from the client database output. This tool would organise the remediation of defects within a given timeline, providing coordinators with a baseline for scheduling jobs.

With this tool, the available information for resourcing the jobs would be enhanced, so it reduced the amount of time that maintenance coordinators required to plan remediations, which in turn would reduce conflicts. What it is also significant is that critical remediations can only be completed when the equipment is turned off. This can negatively impact production goals, because if an entire line is dependent on that asset, there is no iron production during that remediation. Lines are only halted 3 times during the year, so being able to implement strict and robust planning would serve to avoid costly, partially completed or postponed remediations.

The Challenges

In order to have a proper understanding of how coordinators plan remediations, it was necessary to gather as much information from their knowledge and experience as possible, to accurately characterise the governing rules into a set of decision trees, as they pertain to a defect’s remediation work plan. This included rules related to asset replacement date, prioritization of a defect’s remediation, urgency of the remediation, remediation dates, shutdown dates, likelihood of failure of the structure, and the impact of that failure. 

The Solution

Mincka organised a set of workshops with client maintenance coordinators and our team of software developers to map out that knowledge and experience into abstract decision trees. The outcome of the workshops was to essentially “bullet proof” the decision a coordinator made, based on a given set of conditions for a particular defect. This approach was tested and proven with several coordinators, different equipment sets, and various lines of production. At the end of the process, the decision model achieved a 94.7% rate of accuracy.

The next step was to provide a model to the development team, to build a user interface that presented the results. The tool uses raw data from the the client’s database, applies the model and then displays the results in a dashboard that easily allows making changes to planning activities. The tool was built in Microsoft Excel, allowing for high compatibility with existing corporate systems and making it easy to use.

The tool was fully developed in record time (one month), including workshops, coding, implementation of functionalities and testing.

The Impact

The client’s coordinators went from spending days planning to literally just seconds. When using the tool for the first time, they were able to identify several defects that had been postponed many times and were long overdue. The availability of information was significantly increased, resulting in the ability to immediately prioritize the oldest defect remediations into the scope of work.

Nowadays, they jump from their database directly into a timeline for the most important remediations that need to be implemented. The time that is saved is now leveraged to improve the process and manage the workload for the teams in charge of the repairs. The process runs smoothly and with more control, saving both time and operational costs.

With effective planning, lines of production keep running and shutdown periods are leveraged to repair the maximum number of defects. This is only possible with proper scheduling and resourcing, made possible with the Mincka developed tool, and now provides significant value add to the organisation. We appreciate the trust BHP Billiton placed in us and look forward to working with them again.

Fidel Gonzalez